Can Big Data Program Morality in Self-Driving Cars?

You are driving down the street at 35 miles an hour. Suddenly, a dog runs onto the road. Without thinking — because it happens too fast to think — you swerve into oncoming traffic to avoid it, crash into the parked car to your right, or slam on your brakes, knowing that there is almost no chance of avoiding a collision. What do you do?

Now imagine the dog is a child and that you have your own child in the car, and then the same thing happens. Scary, right? How do we make these sudden decisions that happen and then last forever? Who are we when we have no time to consider what to do?

This is not just raw philosophy. It is a question that engineers, programmers and OEMs must think about as they create responsive algorithms for self-driving cars. A self-driving vehicle is, in some ways, a moral agent with a programmed but lesser immediate set of ethics and responsibilities.

How can something so nuanced be programmed? How can a choice like this be made without direct human interaction? The answer potentially (and seemingly paradoxically) lies in the realm of big data – raw numbers that can somehow be transformed into a sense of morality. This is why OEMs need to take big data seriously by creating datasets that allow an actual sense of ethics to develop. To do so, we must also look at how our own ethics and personalities form.

Memory as the Font of Personality

Once, a friend recalled to me one of his first real memories – he was about four and was at his sister’s third birthday party. He wanted her balloon and knocked it out of her hand. Of course, it immediately went soaring up into the sky, to the sound of wailing tears below. The moment stuck with him his entire life, and he has tried (with some success) to never again covet a balloon.

More than that, the childish sadness of the day played a role in his personality. He credits it with making him more cautious and more concerned about people’s feelings. It was not just that one incident, of course; there are thousands of these moments throughout our lives with decisions and revisions that define who we are.

Some psychologists argue that memory is one of the key facets of someone’s personality. At a TED talk, one of the founders of behavioral economics, Nobel Prize-winner Daniel Kahneman, argued that when we think of how to behave “we actually do not choose between experiences, but rather choose between memories of experiences,” meaning that our memory of an experience is more responsible for how we act rather than what actually happened. In other words, memory drives our actions, shaping the reality in which we act.

We know how important this is, instinctively. When a person suffers from Alzheimer’s, we do not just talk about their memory fading in terms of the ability to conjure names and dates, but we also talk about the patient losing a sense of who they are. While some joyful research shows it is still there somewhere, we have accepted that when memory leaves us, we leave ourselves.

Thus, memory plays a crucial role in decision-making when we are on the road and face an unprecedented choice. While most drivers have never been in such a situation, they have been in moral situations before, which have affected who they are and what choices they make, allowing them to instinctively draw from a well of past experiences to make a decision. But how can a car do the same thing? From what well does it draw its decision-making skills?

Memory and Big Data

This is where big data comes in. Big data, in its essence, is a collected memory, a record of experience from all connected devices. Unlike human memory, the experience is not clouded by shame or pride or the usual fog of time. It is captured perfectly.

Big data collection actually mimics memory in some very important ways. As Emily Trinh at Bryn Mawr explains it, “Memory is also defined as the ability to retain information, and it is influenced by three important stages. The first stage is encoding and processing the information, the second stage is the storing of the memory, and the third stage is memory retrieval.”

Let us break that down and apply it to data:

Encoding and processing information: Automakers are already receiving a flood of information from connected cars, and that flood will continue to grow. In a few years, it is estimated that each connected car will produce 2 petabytes of data annually, capturing every rotation of the wheel and every interaction with other cars and the external environment. That data needs to be understood and processed accurately. One of the most innovative ways to do so is with graph databases, which mimic the mind by making quick connections between similar pieces of information.

Storing of the memory: Vast clouds of data need to be stored in a way that can allow the core algorithms powering connected cars to access them immediately. This means that the data cannot just to be dumped away — it must remain easily accessible.

Memory retrieval: This is key. Memory retrieval is not about sitting on the porch and reminiscing. It is about the car calling on a vast database to understand what to do in any given situation. If it is about to hit a pothole when it is raining and there are other vehicles directly adjacent to either side of the car, it has to call on the “memory” of every car who has ever been in such a situation and use this to deduce the right course of action. More than that, it must be able to find similar situations if there is no exact match and decide from there. All of this must happen instantly. It is real-time data.

This is where big data can become a source of morality, an essential set of ethics. The classic scenario dreamed by every ethicist is “What happens if a car has the choice of running into a group of children or killing the driver by swerving into a tree? Or if it must make a choice between hitting one person or two?” It is an example of the “trolley dilemma”. The implication, of course, is that a car does not have the same moral dependency and would fall back on a set code.

What if a broader memory based on big data can create a different set of ethics? What if that vast storage of scenarios means it has already experienced knocking a balloon out of a little girl’s hand, and not only does it never happen again but it can also help anyone else in a similar situation avoid the same mistake? With the collected data of experience, minus the adrenaline and fear, a car might be able to make a moral decision and avoid hitting anything or hurting anyone.

That is the dream and it is potentially achievable. Memories of the car and every other connected car form a vast web of information that can be drawn from, allowing each vehicle to always make the best decision. This is big data, shrunk suddenly down to the most human level.

As the auto industry is changed by technological and economic currents, OEMs and Tier-1 manufacturers will need to partner with technological specialists to thrive in the era of the software defined car. Movimento’s expertise is rooted in our background as an automotive company. This has allowed us to create the technological platform that underpins the future of the software driven and self-driven car. Connect with us today to learn more about how we can work together.